lancelet / TinyHITNet

HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matching

HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matching

This is a Pytorch implementations of "HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matching".

---

Accuracy

Model	Sceneflow Finalpass, EPE	δ<0.1(%)	δ<1.0(%)	δ<3.0(%)	GMac(G)	Checkpoint
HitNet-XL	0.3762	82.1971	96.2759	98.1472	386.6757	ckpt	converted copy of original tensorflow model
HitNet	0.5486	75.1038	94.5830	97.3138	50.5048	ckpt
StereoNet	0.7566	50.0250	91.0111	96.2597	106.7765	ckpt	8x downsample

Training

python3 -m venv venv
source venv/bin/activate
pip install torch

1. Compile and install cuda op

   CC=gcc-10 CXX=g++-10 pip install ./ext_op

2. Replace dataset path in preprocess/plane_fitting.py and script/hitnet_sf_finalpass.sh

3. Robust plane fitting

   python -m preprocess.plane_fitting_sf
   

4. Training

   bash script/hitnet_sf_finalpass.sh

Evaluation

1. Replace dataset path in eval.py

2. Evaluation

   python eval.py --model HITNet --ckpt ckpt/{ckpt_name} --data_type SceneFlow --data_root_val {path} --data_list_val lists/sceneflow_test.list

Predict

python predict.py --model HITNet --ckpt ckpt/{ckpt_name} --images {left.png} {right.png} --output {disp.png}

Citation

@article{tankovich2020hitnet,
  title={HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matching},
  author={Tankovich, Vladimir and H{\"a}ne, Christian and Fanello, Sean and Zhang, Yinda and Izadi, Shahram and Bouaziz, Sofien},
  journal={arXiv preprint arXiv:2007.12140},
  year={2020}
}

However, if you find this implementation or pre-trained models helpful, please consider to cite:

@misc{hang2021tinyhitnet,
  title={TinyHITNet},
  author={zjjMaiMai},
  howpublished={\url{https://github.com/zjjMaiMai/TinyHITNet}},
  year={2021}
}